package com.wz.jiangsu.wangteng.flink;

import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.AggregateOperator;
import org.apache.flink.api.java.operators.DataSource;
import org.apache.flink.api.java.operators.FlatMapOperator;
import org.apache.flink.api.java.operators.UnsortedGrouping;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;

/**
 * @program: event_query
 * @author: wangzhou
 * @create: 2023-11-02 12:02
 * @description:
 **/
public class BatchWordCount {
    public static void main(String[] args) throws Exception{
        // 1. 创建执行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        // 2. 从文件中读取数据
        DataSource<String> lineDataSource = env.readTextFile("C:\\event_query\\input\\words.txt");

        // 3. 将每行数据进行分词，转化成二元数据类型
//        lineDataSource.flatMap((String line, Collector<Tuple2<String,Long>> out) -> )
        FlatMapOperator<String, Tuple2<String, Long>> wordAndOneTuple = lineDataSource.flatMap((String line, Collector<Tuple2<String, Long>> out) -> {
            // 将一行文本进行分词
            String[] words = line.split(" ");
            // 将每个单词转换成二元组进行输出
            for (String word : words) {
                out.collect(Tuple2.of(word, 1L));
            }
        }).returns(Types.TUPLE(Types.STRING, Types.LONG));

        // 4. 按照 word 进行分组
        UnsortedGrouping<Tuple2<String, Long>> wordAndOneGroup = wordAndOneTuple.groupBy(0);

        // 5. 分组内进行聚合统计
        AggregateOperator<Tuple2<String, Long>> sum = wordAndOneGroup.sum(1);

        // 6. 打印输出
        sum.print();

    }
}
